Deep sub-micron technology enables a high integration of (non-linear) circuit systems for electronic products. In order to design non-linear circuits with guaranteed reliability, a sophisticated simulation procedure is required. However, in existing GPU-enhanced circuit simulation methodologies, numerous data transfers between cores hamper the benefits of GPU computations. In this project, we focus on the par- allelization of computations for nonlinear analog/mixed-signal circuit transient simulation. By applying multi-dimensional inverse Laplace Transform, each time-sampled points of the transient response can be computed independently on the GPU architecture. Power-efficient hardware architecture is also explored for a further speedup. With the developed platform, circuit designers can verify circuit's dynamic properties quickly in order to meet the need of time-critical and high-yield designs.

Deep sub-micron technology enables a high integration of (non-linear) circuit systems for electronic products. In order to design non-linear circuits with guaranteed reliability, a sophisticated simulation procedure is required. However, in existing GPU-enhanced circuit simulation methodologies, numerous data transfers between cores hamper the benefits of GPU computations. In this project, we focus on the par- allelization of computations for nonlinear analog/mixed-signal circuit transient simulation. By applying multi-dimensional inverse Laplace Transform, each time-sampled points of the transient response can be computed independently on the GPU architecture. Power-efficient hardware architecture is also explored for a further speedup. With the developed platform, circuit designers can verify circuit's dynamic properties quickly in order to meet the need of time-critical and high-yield designs.